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  • Comprehensive Data-Driven Framework for Statistical Transient Stability Analysis in Variable Inertia Power Systems Enabled by High-Throughput Simulation
  • https://doi.org/10.1109/pree67492.2025.11433894Copy DOI Icon

Comprehensive Data-Driven Framework for Statistical Transient Stability Analysis in Variable Inertia Power Systems Enabled by High-Throughput Simulation

  • Oct 28, 2025
  • Keito Nishida +3 more
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Abstract

The integration of renewable energy reduces electrical power system inertia, increasing vulnerability to disturbances. Conventional transient stability analysis suffers from event selectivity limitations. Hence, predetermined “worst case” scenarios overlook the risk associated with critical vulnerability patterns. This paper demonstrates that high-throughput simulation can systematically explore the entire contingency pattern to identify essential clusters of vulnerability. The automated framework reduces simulation time by 85 % while enabling statistical analysis across different inertia levels (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2 ~\mathrm{s}, 8 ~\mathrm{s}$</tex>, 16s) and disturbance magnitudes (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$250-1000 \text{MW}$</tex>) using the IEEJ EAST 10-machine system. The RoCoF and Nadir results reveal distinct spatial vulnerability clustering, with buses 18, 19, 20, 36, 37, and 47 consistently exhibiting the highest impacts regardless of operating conditions. These topology-dependent vulnerability patterns require comprehensive rather than selective analysis for practical power system security assessment.

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